Credit Card Users Churn Prediction

Thera bank recently saw a steep decline in the number of credit card users. Credit cards are a good source of income for banks because they can charge a variety of fees to the users. Some fees are charged to every user irrespective of usage, while others are charged under specified circumstances.

The loss of credit card clients is affecting the bank's bottom line, so the bank wants to analyze the data of customers and identify the clients who will end their credit card services, so the bank can attempt to retain them as credit card clients.

As a Data scientist for Thera bank, I need to derive a classification model that will help the bank improve its services so that customers do not renounce their credit cards.

Objective

Data Dictionary

Observations

Observations

EDA

Uni-variate

Multi-variate

Building the Models

Observations

Observations

Regularization with RandomizedSearchCV

Final_Model_Train = model_performance_classification_sklearn( Final_Model, X_train_un, y_train_un ) print("Training performance:") Final_Model_Train

Importances

Pipelines

Business Recommendations